Excitement around the Industrial Internet of Things (IIoT) continues to grow. Though manufacturing companies are eager to reap the benefits, they’re still not investing at a pace consistent with their enthusiasm. It’s not that executives don’t sense the tremendous opportunity offered by IIoT. In fact, it’s not even technology issues like scalability or cybersecurity that give them pause. Most companies don’t have pockets deep enough to take big leaps of faith based on sixth-sense, gut-feeling perceptions. It makes sense then that the top two challenges to investing in IIoT are purely financial: building a business case and funding.
This isn’t a new problem, or even one confined to industry. Whenever a new technology comes to light, the scope and scale of benefits is often unknown until after someone starts using it. For example, airplanes were starting to take shape as early as 1799, but it wasn’t until 1903 with the Wright brothers’ first powered flight that the world considered air travel viable. Even then, the Wrights didn’t contact the U.S. government as a potential customer until 1905, and the U.S. Army didn’t buy anything until 1909.
It would be another five years before a businessman recognized the potential value of commercial flight and started the world’s first scheduled passenger airline service operating between St. Petersburg and Tampa, Fla. The regular fare was $5 per person, and for the four months it operated in 1914, the St. Petersburg-Tampa Airboat Line carried a total of 1,205 passengers—netting at least $6,025 in passenger revenue, which is equivalent to more than $145,000 today.
The founders of that first commercial airline didn’t have the benefit of looking elsewhere to discern what the potential financial value of their endeavor might be. It’s entirely possible, though, that later airlines took note of that first company’s success and the value it derived from winged flight technology to build a business case and gather funding for new commercial airline services.
Early adopters of IIoT technologies and early pioneers of digital transformation are a beacon for other industrial companies that are eager to explore the opportunities presented by still-fresh technologies.
Companies interested in digital transformation and IIoT can glean more from these trailblazers than just what they did and how they did it. Applying use cases to a different business does require some creativity, but eliminates the risk of buying on faith. An executive can look to peer companies that are already reaping benefits to make an educated estimate on what the real financial value will be for his or her own company. Let’s examine three use cases studied recently by LNS Research.
Use case 1: supercharging clean-in-place systems
A fast and efficient clean-in-place (CIP) process is a must for any manufacturer that is regulated by the U.S. Food and Drug Administration (FDA) or other governing agency or compliance organization. Effective CIP doesn’t just ensure compliance; it is a means for a manufacturer to increase asset availability and improve overall equipment effectiveness (OEE) while reducing the risk associated with product safety.
One company examined by LNS is using IIoT to rethink CIP. Instead of each local plant assuming a production line is clean after completing a CIP activity, the company uses IIoT to provide global visibility of CIP and measure cleanliness continuously, with the CIP process ending only when the line is clean. This company’s changeover time has averaged four hours per line, and it anticipates a 50 percent or better reduction in changeover time plus a dramatic drop in food safety risk.
Use case 2: applying social, geospatial and asset data
One of the largest rail systems in Europe recently spent two years implementing an IIoT pilot project sensing, connecting and analyzing data from across the network. With an annual maintenance and repair budget of more than €1 billion ($1.12 billion), the agency is already projecting more than 8 percent savings on maintenance. One of the ways they plan to achieve this is simply by turning the train around. By examining logistics, geographic information system (GIS) and asset data, the company discovered that too many trains were running the same routes in the same orientation, which created uneven wear and increased maintenance activities. Prescriptive insights from Big Data analytics are surprisingly simple to implement—like turn the train around.
Meanwhile, a local wastewater utility for a major city in Europe recently started an IIoT project to compare real-time and historical process data with historical and streaming social data. Two early insights from the project revealed correlations in the data that few expected. The organization discovered a correlation between commercial breaks for highly rated TV shows and demand spikes on the system. The insight allowed operators to identify certain increases in demand as temporary and refrain from bringing in extra capacity that wasn’t needed. Some insights allow industrials to anticipate the big flush.
Use case 3: smart products and disrupting quality testing
Our analysts studied one leading smart connected products company that is using new connectivity and intelligence capabilities in its end product to conduct quality testing during production and eliminate previously undetected dead on arrival (DoA) failures from reaching customers’ doorsteps. This approach dramatically reduces the cost of quality testing.
Use cases are just the beginning
These three examples are just a small sample of the use cases now available for companies to leverage when building a business case for investment in digital transformation and IIoT technologies. The secret is to learn about what others have already done or are currently doing, and find ways to make the results they’re getting relevant to your business. There is tremendous value for most organizations, but for each day they wait, another day’s worth of value is lost.
The first step is to determine why the company is still stuck trying to figure out its IIoT strategy, and if the reason is building the business case for investment. The next step is look to peer companies and research analysts to understand digital transformation use cases, entry points, approaches and benefits.
Read more about these and other use cases.
>>Diane Murray is a senior marketing and research associate with LNS Research. Her editorial and marketing efforts span the breadth of LNS coverage areas, including digital transformation and the Industrial Internet of Things (IIoT), along with manufacturing operations management (MOM), asset performance management (APM), quality management, and environment, health and safety (EHS).
